{
    "description": "An agent that can perform question answering over a database",
    "usecases": ["SQL"],
    "nodes": [
        {
            "id": "startAgentflow_0",
            "type": "agentFlow",
            "position": {
                "x": -97,
                "y": 108
            },
            "data": {
                "id": "startAgentflow_0",
                "label": "Start",
                "version": 1.1,
                "name": "startAgentflow",
                "type": "Start",
                "color": "#7EE787",
                "hideInput": true,
                "baseClasses": ["Start"],
                "category": "Agent Flows",
                "description": "Starting point of the agentflow",
                "inputParams": [
                    {
                        "label": "Input Type",
                        "name": "startInputType",
                        "type": "options",
                        "options": [
                            {
                                "label": "Chat Input",
                                "name": "chatInput",
                                "description": "Start the conversation with chat input"
                            },
                            {
                                "label": "Form Input",
                                "name": "formInput",
                                "description": "Start the workflow with form inputs"
                            }
                        ],
                        "default": "chatInput",
                        "id": "startAgentflow_0-input-startInputType-options",
                        "display": true
                    },
                    {
                        "label": "Form Title",
                        "name": "formTitle",
                        "type": "string",
                        "placeholder": "Please Fill Out The Form",
                        "show": {
                            "startInputType": "formInput"
                        },
                        "id": "startAgentflow_0-input-formTitle-string",
                        "display": false
                    },
                    {
                        "label": "Form Description",
                        "name": "formDescription",
                        "type": "string",
                        "placeholder": "Complete all fields below to continue",
                        "show": {
                            "startInputType": "formInput"
                        },
                        "id": "startAgentflow_0-input-formDescription-string",
                        "display": false
                    },
                    {
                        "label": "Form Input Types",
                        "name": "formInputTypes",
                        "description": "Specify the type of form input",
                        "type": "array",
                        "show": {
                            "startInputType": "formInput"
                        },
                        "array": [
                            {
                                "label": "Type",
                                "name": "type",
                                "type": "options",
                                "options": [
                                    {
                                        "label": "String",
                                        "name": "string"
                                    },
                                    {
                                        "label": "Number",
                                        "name": "number"
                                    },
                                    {
                                        "label": "Boolean",
                                        "name": "boolean"
                                    },
                                    {
                                        "label": "Options",
                                        "name": "options"
                                    }
                                ],
                                "default": "string"
                            },
                            {
                                "label": "Label",
                                "name": "label",
                                "type": "string",
                                "placeholder": "Label for the input"
                            },
                            {
                                "label": "Variable Name",
                                "name": "name",
                                "type": "string",
                                "placeholder": "Variable name for the input (must be camel case)",
                                "description": "Variable name must be camel case. For example: firstName, lastName, etc."
                            },
                            {
                                "label": "Add Options",
                                "name": "addOptions",
                                "type": "array",
                                "show": {
                                    "formInputTypes[$index].type": "options"
                                },
                                "array": [
                                    {
                                        "label": "Option",
                                        "name": "option",
                                        "type": "string"
                                    }
                                ]
                            }
                        ],
                        "id": "startAgentflow_0-input-formInputTypes-array",
                        "display": false
                    },
                    {
                        "label": "Ephemeral Memory",
                        "name": "startEphemeralMemory",
                        "type": "boolean",
                        "description": "Start fresh for every execution without past chat history",
                        "optional": true,
                        "id": "startAgentflow_0-input-startEphemeralMemory-boolean",
                        "display": true
                    },
                    {
                        "label": "Flow State",
                        "name": "startState",
                        "description": "Runtime state during the execution of the workflow",
                        "type": "array",
                        "optional": true,
                        "array": [
                            {
                                "label": "Key",
                                "name": "key",
                                "type": "string",
                                "placeholder": "Foo"
                            },
                            {
                                "label": "Value",
                                "name": "value",
                                "type": "string",
                                "placeholder": "Bar",
                                "optional": true
                            }
                        ],
                        "id": "startAgentflow_0-input-startState-array",
                        "display": true
                    },
                    {
                        "label": "Persist State",
                        "name": "startPersistState",
                        "type": "boolean",
                        "description": "Persist the state in the same session",
                        "optional": true,
                        "id": "startAgentflow_0-input-startPersistState-boolean",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "startInputType": "chatInput",
                    "formTitle": "",
                    "formDescription": "",
                    "formInputTypes": "",
                    "startEphemeralMemory": "",
                    "startState": [
                        {
                            "key": "sqlQuery",
                            "value": ""
                        }
                    ],
                    "startPersistState": ""
                },
                "outputAnchors": [
                    {
                        "id": "startAgentflow_0-output-startAgentflow",
                        "label": "Start",
                        "name": "startAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "width": 103,
            "height": 66,
            "selected": false,
            "positionAbsolute": {
                "x": -97,
                "y": 108
            },
            "dragging": false
        },
        {
            "id": "customFunctionAgentflow_0",
            "position": {
                "x": 58.5,
                "y": 109
            },
            "data": {
                "id": "customFunctionAgentflow_0",
                "label": "Get DB Schema",
                "version": 1,
                "name": "customFunctionAgentflow",
                "type": "CustomFunction",
                "color": "#E4B7FF",
                "baseClasses": ["CustomFunction"],
                "category": "Agent Flows",
                "description": "Execute custom function",
                "inputParams": [
                    {
                        "label": "Input Variables",
                        "name": "customFunctionInputVariables",
                        "description": "Input variables can be used in the function with prefix $. For example: $foo",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Variable Name",
                                "name": "variableName",
                                "type": "string"
                            },
                            {
                                "label": "Variable Value",
                                "name": "variableValue",
                                "type": "string",
                                "acceptVariable": true
                            }
                        ],
                        "id": "customFunctionAgentflow_0-input-customFunctionInputVariables-array",
                        "display": true
                    },
                    {
                        "label": "Javascript Function",
                        "name": "customFunctionJavascriptFunction",
                        "type": "code",
                        "codeExample": "/*\n* You can use any libraries imported in Flowise\n* You can use properties specified in Input Schema as variables. Ex: Property = userid, Variable = $userid\n* You can get default flow config: $flow.sessionId, $flow.chatId, $flow.chatflowId, $flow.input, $flow.state\n* You can get custom variables: $vars.<variable-name>\n* Must return a string value at the end of function\n*/\n\nconst fetch = require('node-fetch');\nconst url = 'https://api.open-meteo.com/v1/forecast?latitude=52.52&longitude=13.41&current_weather=true';\nconst options = {\n    method: 'GET',\n    headers: {\n        'Content-Type': 'application/json'\n    }\n};\ntry {\n    const response = await fetch(url, options);\n    const text = await response.text();\n    return text;\n} catch (error) {\n    console.error(error);\n    return '';\n}",
                        "description": "The function to execute. Must return a string or an object that can be converted to a string.",
                        "id": "customFunctionAgentflow_0-input-customFunctionJavascriptFunction-code",
                        "display": true
                    },
                    {
                        "label": "Update Flow State",
                        "name": "customFunctionUpdateState",
                        "description": "Update runtime state during the execution of the workflow",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Key",
                                "name": "key",
                                "type": "asyncOptions",
                                "loadMethod": "listRuntimeStateKeys",
                                "freeSolo": true
                            },
                            {
                                "label": "Value",
                                "name": "value",
                                "type": "string",
                                "acceptVariable": true,
                                "acceptNodeOutputAsVariable": true
                            }
                        ],
                        "id": "customFunctionAgentflow_0-input-customFunctionUpdateState-array",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "customFunctionInputVariables": "",
                    "customFunctionJavascriptFunction": "const { DataSource } = require('typeorm');\nconst { Pool } = require('pg');\n\nconst HOST = 'localhost';\nconst USER = 'testuser';\nconst PASSWORD = 'testpwd';\nconst DATABASE = 'abudhabi';\nconst PORT = 5555;\n\nlet sqlSchemaPrompt = '';\n\nconst AppDataSource = new DataSource({\n  type: 'postgres',\n  host: HOST,\n  port: PORT,\n  username: USER,\n  password: PASSWORD,\n  database: DATABASE,\n  synchronize: false,\n  logging: false,\n});\n\nasync function getSQLPrompt() {\n  try {\n    await AppDataSource.initialize();\n    const queryRunner = AppDataSource.createQueryRunner();\n\n    // Get all user-defined tables (excluding system tables)\n    const tablesResult = await queryRunner.query(`\n      SELECT table_name\n      FROM information_schema.tables\n      WHERE table_schema = 'public' AND table_type = 'BASE TABLE'\n    `);\n\n    for (const tableRow of tablesResult) {\n      const tableName = tableRow.table_name;\n\n      const schemaInfo = await queryRunner.query(`\n        SELECT column_name, data_type, is_nullable\n        FROM information_schema.columns\n        WHERE table_name = '${tableName}'\n      `);\n\n      const createColumns = [];\n      const columnNames = [];\n\n      for (const column of schemaInfo) {\n        const name = column.column_name;\n        const type = column.data_type.toUpperCase();\n        const notNull = column.is_nullable === 'NO' ? 'NOT NULL' : '';\n        columnNames.push(name);\n        createColumns.push(`${name} ${type} ${notNull}`);\n      }\n\n      const sqlCreateTableQuery = `CREATE TABLE ${tableName} (${createColumns.join(', ')})`;\n      const sqlSelectTableQuery = `SELECT * FROM ${tableName} LIMIT 3`;\n\n      let allValues = [];\n      try {\n        const rows = await queryRunner.query(sqlSelectTableQuery);\n\n        allValues = rows.map(row =>\n          columnNames.map(col => row[col]).join(' ')\n        );\n      } catch (err) {\n        allValues.push('[ERROR FETCHING ROWS]');\n      }\n\n      sqlSchemaPrompt +=\n        sqlCreateTableQuery +\n        '\\n' +\n        sqlSelectTableQuery +\n        '\\n' +\n        columnNames.join(' ') +\n        '\\n' +\n        allValues.join('\\n') +\n        '\\n\\n';\n    }\n\n    await queryRunner.release();\n  } catch (err) {\n    console.error(err);\n    throw err;\n  }\n}\n\nasync function main() {\n  await getSQLPrompt();\n}\n\nawait main();\n\nreturn sqlSchemaPrompt;\n",
                    "customFunctionUpdateState": ""
                },
                "outputAnchors": [
                    {
                        "id": "customFunctionAgentflow_0-output-customFunctionAgentflow",
                        "label": "Custom Function",
                        "name": "customFunctionAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "type": "agentFlow",
            "width": 173,
            "height": 66,
            "selected": false,
            "positionAbsolute": {
                "x": 58.5,
                "y": 109
            },
            "dragging": false
        },
        {
            "id": "llmAgentflow_0",
            "position": {
                "x": 272.7184381707814,
                "y": 106.61165168988839
            },
            "data": {
                "id": "llmAgentflow_0",
                "label": "Generate SQL Query",
                "version": 1,
                "name": "llmAgentflow",
                "type": "LLM",
                "color": "#64B5F6",
                "baseClasses": ["LLM"],
                "category": "Agent Flows",
                "description": "Large language models to analyze user-provided inputs and generate responses",
                "inputParams": [
                    {
                        "label": "Model",
                        "name": "llmModel",
                        "type": "asyncOptions",
                        "loadMethod": "listModels",
                        "loadConfig": true,
                        "id": "llmAgentflow_0-input-llmModel-asyncOptions",
                        "display": true
                    },
                    {
                        "label": "Messages",
                        "name": "llmMessages",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Role",
                                "name": "role",
                                "type": "options",
                                "options": [
                                    {
                                        "label": "System",
                                        "name": "system"
                                    },
                                    {
                                        "label": "Assistant",
                                        "name": "assistant"
                                    },
                                    {
                                        "label": "Developer",
                                        "name": "developer"
                                    },
                                    {
                                        "label": "User",
                                        "name": "user"
                                    }
                                ]
                            },
                            {
                                "label": "Content",
                                "name": "content",
                                "type": "string",
                                "acceptVariable": true,
                                "generateInstruction": true,
                                "rows": 4
                            }
                        ],
                        "id": "llmAgentflow_0-input-llmMessages-array",
                        "display": true
                    },
                    {
                        "label": "Enable Memory",
                        "name": "llmEnableMemory",
                        "type": "boolean",
                        "description": "Enable memory for the conversation thread",
                        "default": true,
                        "optional": true,
                        "id": "llmAgentflow_0-input-llmEnableMemory-boolean",
                        "display": true
                    },
                    {
                        "label": "Memory Type",
                        "name": "llmMemoryType",
                        "type": "options",
                        "options": [
                            {
                                "label": "All Messages",
                                "name": "allMessages",
                                "description": "Retrieve all messages from the conversation"
                            },
                            {
                                "label": "Window Size",
                                "name": "windowSize",
                                "description": "Uses a fixed window size to surface the last N messages"
                            },
                            {
                                "label": "Conversation Summary",
                                "name": "conversationSummary",
                                "description": "Summarizes the whole conversation"
                            },
                            {
                                "label": "Conversation Summary Buffer",
                                "name": "conversationSummaryBuffer",
                                "description": "Summarize conversations once token limit is reached. Default to 2000"
                            }
                        ],
                        "optional": true,
                        "default": "allMessages",
                        "show": {
                            "llmEnableMemory": true
                        },
                        "id": "llmAgentflow_0-input-llmMemoryType-options",
                        "display": true
                    },
                    {
                        "label": "Window Size",
                        "name": "llmMemoryWindowSize",
                        "type": "number",
                        "default": "20",
                        "description": "Uses a fixed window size to surface the last N messages",
                        "show": {
                            "llmMemoryType": "windowSize"
                        },
                        "id": "llmAgentflow_0-input-llmMemoryWindowSize-number",
                        "display": false
                    },
                    {
                        "label": "Max Token Limit",
                        "name": "llmMemoryMaxTokenLimit",
                        "type": "number",
                        "default": "2000",
                        "description": "Summarize conversations once token limit is reached. Default to 2000",
                        "show": {
                            "llmMemoryType": "conversationSummaryBuffer"
                        },
                        "id": "llmAgentflow_0-input-llmMemoryMaxTokenLimit-number",
                        "display": false
                    },
                    {
                        "label": "Input Message",
                        "name": "llmUserMessage",
                        "type": "string",
                        "description": "Add an input message as user message at the end of the conversation",
                        "rows": 4,
                        "optional": true,
                        "acceptVariable": true,
                        "show": {
                            "llmEnableMemory": true
                        },
                        "id": "llmAgentflow_0-input-llmUserMessage-string",
                        "display": true
                    },
                    {
                        "label": "Return Response As",
                        "name": "llmReturnResponseAs",
                        "type": "options",
                        "options": [
                            {
                                "label": "User Message",
                                "name": "userMessage"
                            },
                            {
                                "label": "Assistant Message",
                                "name": "assistantMessage"
                            }
                        ],
                        "default": "userMessage",
                        "id": "llmAgentflow_0-input-llmReturnResponseAs-options",
                        "display": true
                    },
                    {
                        "label": "JSON Structured Output",
                        "name": "llmStructuredOutput",
                        "description": "Instruct the LLM to give output in a JSON structured schema",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Key",
                                "name": "key",
                                "type": "string"
                            },
                            {
                                "label": "Type",
                                "name": "type",
                                "type": "options",
                                "options": [
                                    {
                                        "label": "String",
                                        "name": "string"
                                    },
                                    {
                                        "label": "String Array",
                                        "name": "stringArray"
                                    },
                                    {
                                        "label": "Number",
                                        "name": "number"
                                    },
                                    {
                                        "label": "Boolean",
                                        "name": "boolean"
                                    },
                                    {
                                        "label": "Enum",
                                        "name": "enum"
                                    },
                                    {
                                        "label": "JSON Array",
                                        "name": "jsonArray"
                                    }
                                ]
                            },
                            {
                                "label": "Enum Values",
                                "name": "enumValues",
                                "type": "string",
                                "placeholder": "value1, value2, value3",
                                "description": "Enum values. Separated by comma",
                                "optional": true,
                                "show": {
                                    "llmStructuredOutput[$index].type": "enum"
                                }
                            },
                            {
                                "label": "JSON Schema",
                                "name": "jsonSchema",
                                "type": "code",
                                "placeholder": "{\n    \"answer\": {\n        \"type\": \"string\",\n        \"description\": \"Value of the answer\"\n    },\n    \"reason\": {\n        \"type\": \"string\",\n        \"description\": \"Reason for the answer\"\n    },\n    \"optional\": {\n        \"type\": \"boolean\"\n    },\n    \"count\": {\n        \"type\": \"number\"\n    },\n    \"children\": {\n        \"type\": \"array\",\n        \"items\": {\n            \"type\": \"object\",\n            \"properties\": {\n                \"value\": {\n                    \"type\": \"string\",\n                    \"description\": \"Value of the children's answer\"\n                }\n            }\n        }\n    }\n}",
                                "description": "JSON schema for the structured output",
                                "optional": true,
                                "show": {
                                    "llmStructuredOutput[$index].type": "jsonArray"
                                }
                            },
                            {
                                "label": "Description",
                                "name": "description",
                                "type": "string",
                                "placeholder": "Description of the key"
                            }
                        ],
                        "id": "llmAgentflow_0-input-llmStructuredOutput-array",
                        "display": true
                    },
                    {
                        "label": "Update Flow State",
                        "name": "llmUpdateState",
                        "description": "Update runtime state during the execution of the workflow",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Key",
                                "name": "key",
                                "type": "asyncOptions",
                                "loadMethod": "listRuntimeStateKeys",
                                "freeSolo": true
                            },
                            {
                                "label": "Value",
                                "name": "value",
                                "type": "string",
                                "acceptVariable": true,
                                "acceptNodeOutputAsVariable": true
                            }
                        ],
                        "id": "llmAgentflow_0-input-llmUpdateState-array",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "llmModel": "chatAnthropic",
                    "llmMessages": [
                        {
                            "role": "system",
                            "content": "<p>You are an agent designed to interact with a SQL database. Given an input question, create a syntactically correct sqlite query to run, then look at the results of the query and return the answer. Unless the user specifies a specific number of examples they wish to obtain, always limit your query to at most 5 results. You can order the results by a relevant column to return the most interesting examples in the database. Never query for all the columns from a specific table, only ask for the relevant columns given the question. DO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.</p><p>Here is the relevant table info:</p><p><span class=\"variable\" data-type=\"mention\" data-id=\"customFunctionAgentflow_0\" data-label=\"customFunctionAgentflow_0\">{{ customFunctionAgentflow_0 }}</span></p><p>Note:</p><ul><li><p> Only generate ONE SQL query</p></li></ul><p></p>"
                        }
                    ],
                    "llmEnableMemory": true,
                    "llmMemoryType": "allMessages",
                    "llmUserMessage": "",
                    "llmReturnResponseAs": "userMessage",
                    "llmStructuredOutput": [
                        {
                            "key": "sql_query",
                            "type": "string",
                            "enumValues": "",
                            "jsonSchema": "",
                            "description": "SQL query"
                        }
                    ],
                    "llmUpdateState": [
                        {
                            "key": "sqlQuery",
                            "value": "<p><span class=\"variable\" data-type=\"mention\" data-id=\"output.sql_query\" data-label=\"output.sql_query\">{{ output.sql_query }}</span> </p>"
                        }
                    ],
                    "llmModelConfig": {
                        "credential": "",
                        "modelName": "claude-sonnet-4-0",
                        "temperature": 0.9,
                        "streaming": true,
                        "maxTokensToSample": "",
                        "topP": "",
                        "topK": "",
                        "extendedThinking": "",
                        "budgetTokens": 1024,
                        "allowImageUploads": "",
                        "llmModel": "chatAnthropic"
                    }
                },
                "outputAnchors": [
                    {
                        "id": "llmAgentflow_0-output-llmAgentflow",
                        "label": "LLM",
                        "name": "llmAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "type": "agentFlow",
            "width": 213,
            "height": 72,
            "selected": false,
            "positionAbsolute": {
                "x": 272.7184381707814,
                "y": 106.61165168988839
            },
            "dragging": false
        },
        {
            "id": "conditionAgentAgentflow_0",
            "position": {
                "x": 511.16504493033483,
                "y": 101.98220225318451
            },
            "data": {
                "id": "conditionAgentAgentflow_0",
                "label": "Check SQL Query",
                "version": 1,
                "name": "conditionAgentAgentflow",
                "type": "ConditionAgent",
                "color": "#ff8fab",
                "baseClasses": ["ConditionAgent"],
                "category": "Agent Flows",
                "description": "Utilize an agent to split flows based on dynamic conditions",
                "inputParams": [
                    {
                        "label": "Model",
                        "name": "conditionAgentModel",
                        "type": "asyncOptions",
                        "loadMethod": "listModels",
                        "loadConfig": true,
                        "id": "conditionAgentAgentflow_0-input-conditionAgentModel-asyncOptions",
                        "display": true
                    },
                    {
                        "label": "Instructions",
                        "name": "conditionAgentInstructions",
                        "type": "string",
                        "description": "A general instructions of what the condition agent should do",
                        "rows": 4,
                        "acceptVariable": true,
                        "placeholder": "Determine if the user is interested in learning about AI",
                        "id": "conditionAgentAgentflow_0-input-conditionAgentInstructions-string",
                        "display": true
                    },
                    {
                        "label": "Input",
                        "name": "conditionAgentInput",
                        "type": "string",
                        "description": "Input to be used for the condition agent",
                        "rows": 4,
                        "acceptVariable": true,
                        "default": "<p><span class=\"variable\" data-type=\"mention\" data-id=\"question\" data-label=\"question\">{{ question }}</span> </p>",
                        "id": "conditionAgentAgentflow_0-input-conditionAgentInput-string",
                        "display": true
                    },
                    {
                        "label": "Scenarios",
                        "name": "conditionAgentScenarios",
                        "description": "Define the scenarios that will be used as the conditions to split the flow",
                        "type": "array",
                        "array": [
                            {
                                "label": "Scenario",
                                "name": "scenario",
                                "type": "string",
                                "placeholder": "User is asking for a pizza"
                            }
                        ],
                        "default": [
                            {
                                "scenario": "SQL query is correct and does not contains mistakes"
                            },
                            {
                                "scenario": "SQL query contains mistakes"
                            }
                        ],
                        "id": "conditionAgentAgentflow_0-input-conditionAgentScenarios-array",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "conditionAgentModel": "chatOpenAI",
                    "conditionAgentInstructions": "<p>You are a SQL expert with a strong attention to detail. Double check the SQL query for common mistakes, including:</p><p>- Using NOT IN with NULL values</p><p>- Using UNION when UNION ALL should have been used</p><p>- Using BETWEEN for exclusive ranges</p><p>- Data type mismatch in predicates</p><p>- Properly quoting identifiers</p><p>- Using the correct number of arguments for functions</p><p>- Casting to the correct data type</p><p>- Using the proper columns for joins</p>",
                    "conditionAgentInput": "<p><span class=\"variable\" data-type=\"mention\" data-id=\"$flow.state.sqlQuery\" data-label=\"$flow.state.sqlQuery\">{{ $flow.state.sqlQuery }}</span> </p>",
                    "conditionAgentScenarios": [
                        {
                            "scenario": "SQL query is correct and does not contains mistakes"
                        },
                        {
                            "scenario": "SQL query contains mistakes"
                        }
                    ],
                    "conditionAgentModelConfig": {
                        "credential": "",
                        "modelName": "gpt-4o-mini",
                        "temperature": 0.9,
                        "streaming": true,
                        "maxTokens": "",
                        "topP": "",
                        "frequencyPenalty": "",
                        "presencePenalty": "",
                        "timeout": "",
                        "strictToolCalling": "",
                        "stopSequence": "",
                        "basepath": "",
                        "proxyUrl": "",
                        "baseOptions": "",
                        "allowImageUploads": "",
                        "imageResolution": "low",
                        "reasoningEffort": "",
                        "conditionAgentModel": "chatOpenAI"
                    }
                },
                "outputAnchors": [
                    {
                        "id": "conditionAgentAgentflow_0-output-0",
                        "label": "Condition Agent",
                        "name": "conditionAgentAgentflow"
                    },
                    {
                        "id": "conditionAgentAgentflow_0-output-1",
                        "label": "Condition Agent",
                        "name": "conditionAgentAgentflow"
                    }
                ],
                "outputs": {
                    "conditionAgentAgentflow": ""
                },
                "selected": false
            },
            "type": "agentFlow",
            "width": 187,
            "height": 80,
            "selected": false,
            "positionAbsolute": {
                "x": 511.16504493033483,
                "y": 101.98220225318451
            },
            "dragging": false
        },
        {
            "id": "loopAgentflow_0",
            "position": {
                "x": 762.44734302386,
                "y": 182.95996068910745
            },
            "data": {
                "id": "loopAgentflow_0",
                "label": "Regenerate Query",
                "version": 1,
                "name": "loopAgentflow",
                "type": "Loop",
                "color": "#FFA07A",
                "hideOutput": true,
                "baseClasses": ["Loop"],
                "category": "Agent Flows",
                "description": "Loop back to a previous node",
                "inputParams": [
                    {
                        "label": "Loop Back To",
                        "name": "loopBackToNode",
                        "type": "asyncOptions",
                        "loadMethod": "listPreviousNodes",
                        "freeSolo": true,
                        "id": "loopAgentflow_0-input-loopBackToNode-asyncOptions",
                        "display": true
                    },
                    {
                        "label": "Max Loop Count",
                        "name": "maxLoopCount",
                        "type": "number",
                        "default": 5,
                        "id": "loopAgentflow_0-input-maxLoopCount-number",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "loopBackToNode": "llmAgentflow_0-Generate SQL Query",
                    "maxLoopCount": 5
                },
                "outputAnchors": [],
                "outputs": {},
                "selected": false
            },
            "type": "agentFlow",
            "width": 190,
            "height": 66,
            "selected": false,
            "positionAbsolute": {
                "x": 762.44734302386,
                "y": 182.95996068910745
            },
            "dragging": false
        },
        {
            "id": "customFunctionAgentflow_1",
            "position": {
                "x": 761.3261621815544,
                "y": 44.65096212173265
            },
            "data": {
                "id": "customFunctionAgentflow_1",
                "label": "Run SQL Query",
                "version": 1,
                "name": "customFunctionAgentflow",
                "type": "CustomFunction",
                "color": "#E4B7FF",
                "baseClasses": ["CustomFunction"],
                "category": "Agent Flows",
                "description": "Execute custom function",
                "inputParams": [
                    {
                        "label": "Input Variables",
                        "name": "customFunctionInputVariables",
                        "description": "Input variables can be used in the function with prefix $. For example: $foo",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Variable Name",
                                "name": "variableName",
                                "type": "string"
                            },
                            {
                                "label": "Variable Value",
                                "name": "variableValue",
                                "type": "string",
                                "acceptVariable": true
                            }
                        ],
                        "id": "customFunctionAgentflow_1-input-customFunctionInputVariables-array",
                        "display": true
                    },
                    {
                        "label": "Javascript Function",
                        "name": "customFunctionJavascriptFunction",
                        "type": "code",
                        "codeExample": "/*\n* You can use any libraries imported in Flowise\n* You can use properties specified in Input Schema as variables. Ex: Property = userid, Variable = $userid\n* You can get default flow config: $flow.sessionId, $flow.chatId, $flow.chatflowId, $flow.input, $flow.state\n* You can get custom variables: $vars.<variable-name>\n* Must return a string value at the end of function\n*/\n\nconst fetch = require('node-fetch');\nconst url = 'https://api.open-meteo.com/v1/forecast?latitude=52.52&longitude=13.41&current_weather=true';\nconst options = {\n    method: 'GET',\n    headers: {\n        'Content-Type': 'application/json'\n    }\n};\ntry {\n    const response = await fetch(url, options);\n    const text = await response.text();\n    return text;\n} catch (error) {\n    console.error(error);\n    return '';\n}",
                        "description": "The function to execute. Must return a string or an object that can be converted to a string.",
                        "id": "customFunctionAgentflow_1-input-customFunctionJavascriptFunction-code",
                        "display": true
                    },
                    {
                        "label": "Update Flow State",
                        "name": "customFunctionUpdateState",
                        "description": "Update runtime state during the execution of the workflow",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Key",
                                "name": "key",
                                "type": "asyncOptions",
                                "loadMethod": "listRuntimeStateKeys",
                                "freeSolo": true
                            },
                            {
                                "label": "Value",
                                "name": "value",
                                "type": "string",
                                "acceptVariable": true,
                                "acceptNodeOutputAsVariable": true
                            }
                        ],
                        "id": "customFunctionAgentflow_1-input-customFunctionUpdateState-array",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "customFunctionInputVariables": [
                        {
                            "variableName": "sqlQuery",
                            "variableValue": "<p><span class=\"variable\" data-type=\"mention\" data-id=\"$flow.state.sqlQuery\" data-label=\"$flow.state.sqlQuery\">{{ $flow.state.sqlQuery }}</span> </p>"
                        }
                    ],
                    "customFunctionJavascriptFunction": "const { DataSource } = require('typeorm');\nconst { Pool } = require('pg');\n\n// Configuration\nconst HOST = 'localhost';\nconst USER = 'testuser';\nconst PASSWORD = 'testpwd';\nconst DATABASE = 'abudhabi';\nconst PORT = 5555;\n\nconst sqlQuery = $sqlQuery;\n\nconst AppDataSource = new DataSource({\n  type: 'postgres',\n  host: HOST,\n  port: PORT,\n  username: USER,\n  password: PASSWORD,\n  database: DATABASE,\n  synchronize: false,\n  logging: false,\n});\n\nlet formattedResult = '';\n\nasync function runSQLQuery(query) {\n  try {\n    await AppDataSource.initialize();\n    const queryRunner = AppDataSource.createQueryRunner();\n\n    const rows = await queryRunner.query(query);\n    console.log('rows =', rows);\n\n    if (rows.length === 0) {\n      formattedResult = '[No results returned]';\n    } else {\n      const columnNames = Object.keys(rows[0]);\n      const header = columnNames.join(' ');\n      const values = rows.map(row =>\n        columnNames.map(col => row[col]).join(' ')\n      );\n\n      formattedResult = query + '\\n' + header + '\\n' + values.join('\\n');\n    }\n\n    await queryRunner.release();\n  } catch (err) {\n    console.error('[ERROR]', err);\n    formattedResult = `[Error executing query]: ${err}`;\n  }\n\n  return formattedResult;\n}\n\nasync function main() {\n  formattedResult = await runSQLQuery(sqlQuery);\n}\n\nawait main();\n\nreturn formattedResult;\n",
                    "customFunctionUpdateState": ""
                },
                "outputAnchors": [
                    {
                        "id": "customFunctionAgentflow_1-output-customFunctionAgentflow",
                        "label": "Custom Function",
                        "name": "customFunctionAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "type": "agentFlow",
            "width": 171,
            "height": 66,
            "selected": false,
            "positionAbsolute": {
                "x": 761.3261621815544,
                "y": 44.65096212173265
            },
            "dragging": false
        },
        {
            "id": "llmAgentflow_1",
            "position": {
                "x": 1238.7660285501179,
                "y": 20.56658816269558
            },
            "data": {
                "id": "llmAgentflow_1",
                "label": "Return Response",
                "version": 1,
                "name": "llmAgentflow",
                "type": "LLM",
                "color": "#64B5F6",
                "baseClasses": ["LLM"],
                "category": "Agent Flows",
                "description": "Large language models to analyze user-provided inputs and generate responses",
                "inputParams": [
                    {
                        "label": "Model",
                        "name": "llmModel",
                        "type": "asyncOptions",
                        "loadMethod": "listModels",
                        "loadConfig": true,
                        "id": "llmAgentflow_1-input-llmModel-asyncOptions",
                        "display": true
                    },
                    {
                        "label": "Messages",
                        "name": "llmMessages",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Role",
                                "name": "role",
                                "type": "options",
                                "options": [
                                    {
                                        "label": "System",
                                        "name": "system"
                                    },
                                    {
                                        "label": "Assistant",
                                        "name": "assistant"
                                    },
                                    {
                                        "label": "Developer",
                                        "name": "developer"
                                    },
                                    {
                                        "label": "User",
                                        "name": "user"
                                    }
                                ]
                            },
                            {
                                "label": "Content",
                                "name": "content",
                                "type": "string",
                                "acceptVariable": true,
                                "generateInstruction": true,
                                "rows": 4
                            }
                        ],
                        "id": "llmAgentflow_1-input-llmMessages-array",
                        "display": true
                    },
                    {
                        "label": "Enable Memory",
                        "name": "llmEnableMemory",
                        "type": "boolean",
                        "description": "Enable memory for the conversation thread",
                        "default": true,
                        "optional": true,
                        "id": "llmAgentflow_1-input-llmEnableMemory-boolean",
                        "display": true
                    },
                    {
                        "label": "Memory Type",
                        "name": "llmMemoryType",
                        "type": "options",
                        "options": [
                            {
                                "label": "All Messages",
                                "name": "allMessages",
                                "description": "Retrieve all messages from the conversation"
                            },
                            {
                                "label": "Window Size",
                                "name": "windowSize",
                                "description": "Uses a fixed window size to surface the last N messages"
                            },
                            {
                                "label": "Conversation Summary",
                                "name": "conversationSummary",
                                "description": "Summarizes the whole conversation"
                            },
                            {
                                "label": "Conversation Summary Buffer",
                                "name": "conversationSummaryBuffer",
                                "description": "Summarize conversations once token limit is reached. Default to 2000"
                            }
                        ],
                        "optional": true,
                        "default": "allMessages",
                        "show": {
                            "llmEnableMemory": true
                        },
                        "id": "llmAgentflow_1-input-llmMemoryType-options",
                        "display": true
                    },
                    {
                        "label": "Window Size",
                        "name": "llmMemoryWindowSize",
                        "type": "number",
                        "default": "20",
                        "description": "Uses a fixed window size to surface the last N messages",
                        "show": {
                            "llmMemoryType": "windowSize"
                        },
                        "id": "llmAgentflow_1-input-llmMemoryWindowSize-number",
                        "display": false
                    },
                    {
                        "label": "Max Token Limit",
                        "name": "llmMemoryMaxTokenLimit",
                        "type": "number",
                        "default": "2000",
                        "description": "Summarize conversations once token limit is reached. Default to 2000",
                        "show": {
                            "llmMemoryType": "conversationSummaryBuffer"
                        },
                        "id": "llmAgentflow_1-input-llmMemoryMaxTokenLimit-number",
                        "display": false
                    },
                    {
                        "label": "Input Message",
                        "name": "llmUserMessage",
                        "type": "string",
                        "description": "Add an input message as user message at the end of the conversation",
                        "rows": 4,
                        "optional": true,
                        "acceptVariable": true,
                        "show": {
                            "llmEnableMemory": true
                        },
                        "id": "llmAgentflow_1-input-llmUserMessage-string",
                        "display": true
                    },
                    {
                        "label": "Return Response As",
                        "name": "llmReturnResponseAs",
                        "type": "options",
                        "options": [
                            {
                                "label": "User Message",
                                "name": "userMessage"
                            },
                            {
                                "label": "Assistant Message",
                                "name": "assistantMessage"
                            }
                        ],
                        "default": "userMessage",
                        "id": "llmAgentflow_1-input-llmReturnResponseAs-options",
                        "display": true
                    },
                    {
                        "label": "JSON Structured Output",
                        "name": "llmStructuredOutput",
                        "description": "Instruct the LLM to give output in a JSON structured schema",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Key",
                                "name": "key",
                                "type": "string"
                            },
                            {
                                "label": "Type",
                                "name": "type",
                                "type": "options",
                                "options": [
                                    {
                                        "label": "String",
                                        "name": "string"
                                    },
                                    {
                                        "label": "String Array",
                                        "name": "stringArray"
                                    },
                                    {
                                        "label": "Number",
                                        "name": "number"
                                    },
                                    {
                                        "label": "Boolean",
                                        "name": "boolean"
                                    },
                                    {
                                        "label": "Enum",
                                        "name": "enum"
                                    },
                                    {
                                        "label": "JSON Array",
                                        "name": "jsonArray"
                                    }
                                ]
                            },
                            {
                                "label": "Enum Values",
                                "name": "enumValues",
                                "type": "string",
                                "placeholder": "value1, value2, value3",
                                "description": "Enum values. Separated by comma",
                                "optional": true,
                                "show": {
                                    "llmStructuredOutput[$index].type": "enum"
                                }
                            },
                            {
                                "label": "JSON Schema",
                                "name": "jsonSchema",
                                "type": "code",
                                "placeholder": "{\n    \"answer\": {\n        \"type\": \"string\",\n        \"description\": \"Value of the answer\"\n    },\n    \"reason\": {\n        \"type\": \"string\",\n        \"description\": \"Reason for the answer\"\n    },\n    \"optional\": {\n        \"type\": \"boolean\"\n    },\n    \"count\": {\n        \"type\": \"number\"\n    },\n    \"children\": {\n        \"type\": \"array\",\n        \"items\": {\n            \"type\": \"object\",\n            \"properties\": {\n                \"value\": {\n                    \"type\": \"string\",\n                    \"description\": \"Value of the children's answer\"\n                }\n            }\n        }\n    }\n}",
                                "description": "JSON schema for the structured output",
                                "optional": true,
                                "show": {
                                    "llmStructuredOutput[$index].type": "jsonArray"
                                }
                            },
                            {
                                "label": "Description",
                                "name": "description",
                                "type": "string",
                                "placeholder": "Description of the key"
                            }
                        ],
                        "id": "llmAgentflow_1-input-llmStructuredOutput-array",
                        "display": true
                    },
                    {
                        "label": "Update Flow State",
                        "name": "llmUpdateState",
                        "description": "Update runtime state during the execution of the workflow",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Key",
                                "name": "key",
                                "type": "asyncOptions",
                                "loadMethod": "listRuntimeStateKeys",
                                "freeSolo": true
                            },
                            {
                                "label": "Value",
                                "name": "value",
                                "type": "string",
                                "acceptVariable": true,
                                "acceptNodeOutputAsVariable": true
                            }
                        ],
                        "id": "llmAgentflow_1-input-llmUpdateState-array",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "llmModel": "chatGoogleGenerativeAI",
                    "llmMessages": [],
                    "llmEnableMemory": true,
                    "llmMemoryType": "allMessages",
                    "llmUserMessage": "<p><span class=\"variable\" data-type=\"mention\" data-id=\"customFunctionAgentflow_1\" data-label=\"customFunctionAgentflow_1\">{{ customFunctionAgentflow_1 }}</span> </p>",
                    "llmReturnResponseAs": "userMessage",
                    "llmStructuredOutput": "",
                    "llmUpdateState": "",
                    "llmModelConfig": {
                        "credential": "",
                        "modelName": "gemini-2.0-flash",
                        "customModelName": "",
                        "temperature": 0.9,
                        "streaming": true,
                        "maxOutputTokens": "",
                        "topP": "",
                        "topK": "",
                        "harmCategory": "",
                        "harmBlockThreshold": "",
                        "baseUrl": "",
                        "allowImageUploads": "",
                        "llmModel": "chatGoogleGenerativeAI"
                    },
                    "undefined": ""
                },
                "outputAnchors": [
                    {
                        "id": "llmAgentflow_1-output-llmAgentflow",
                        "label": "LLM",
                        "name": "llmAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "type": "agentFlow",
            "width": 199,
            "height": 72,
            "selected": false,
            "positionAbsolute": {
                "x": 1238.7660285501179,
                "y": 20.56658816269558
            },
            "dragging": false
        },
        {
            "id": "conditionAgentAgentflow_1",
            "position": {
                "x": 966.5436041632489,
                "y": 57.77868724229256
            },
            "data": {
                "id": "conditionAgentAgentflow_1",
                "label": "Check Result",
                "version": 1,
                "name": "conditionAgentAgentflow",
                "type": "ConditionAgent",
                "color": "#ff8fab",
                "baseClasses": ["ConditionAgent"],
                "category": "Agent Flows",
                "description": "Utilize an agent to split flows based on dynamic conditions",
                "inputParams": [
                    {
                        "label": "Model",
                        "name": "conditionAgentModel",
                        "type": "asyncOptions",
                        "loadMethod": "listModels",
                        "loadConfig": true,
                        "id": "conditionAgentAgentflow_1-input-conditionAgentModel-asyncOptions",
                        "display": true
                    },
                    {
                        "label": "Instructions",
                        "name": "conditionAgentInstructions",
                        "type": "string",
                        "description": "A general instructions of what the condition agent should do",
                        "rows": 4,
                        "acceptVariable": true,
                        "placeholder": "Determine if the user is interested in learning about AI",
                        "id": "conditionAgentAgentflow_1-input-conditionAgentInstructions-string",
                        "display": true
                    },
                    {
                        "label": "Input",
                        "name": "conditionAgentInput",
                        "type": "string",
                        "description": "Input to be used for the condition agent",
                        "rows": 4,
                        "acceptVariable": true,
                        "default": "<p><span class=\"variable\" data-type=\"mention\" data-id=\"question\" data-label=\"question\">{{ question }}</span> </p>",
                        "id": "conditionAgentAgentflow_1-input-conditionAgentInput-string",
                        "display": true
                    },
                    {
                        "label": "Scenarios",
                        "name": "conditionAgentScenarios",
                        "description": "Define the scenarios that will be used as the conditions to split the flow",
                        "type": "array",
                        "array": [
                            {
                                "label": "Scenario",
                                "name": "scenario",
                                "type": "string",
                                "placeholder": "User is asking for a pizza"
                            }
                        ],
                        "default": [
                            {
                                "scenario": "Result is correct and does not contains error"
                            },
                            {
                                "scenario": "Result query contains error"
                            }
                        ],
                        "id": "conditionAgentAgentflow_1-input-conditionAgentScenarios-array",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "conditionAgentModel": "chatMistralAI",
                    "conditionAgentInstructions": "<p>You are a SQL expert. Check if the query result is correct or contains error.</p>",
                    "conditionAgentInput": "<p><span class=\"variable\" data-type=\"mention\" data-id=\"customFunctionAgentflow_1\" data-label=\"customFunctionAgentflow_1\">{{ customFunctionAgentflow_1 }}</span> </p>",
                    "conditionAgentScenarios": [
                        {
                            "scenario": "Result is correct and does not contains error"
                        },
                        {
                            "scenario": "Result query contains error"
                        }
                    ],
                    "conditionAgentModelConfig": {
                        "credential": "",
                        "modelName": "mistral-medium-latest",
                        "temperature": 0.9,
                        "streaming": true,
                        "maxOutputTokens": "",
                        "topP": "",
                        "randomSeed": "",
                        "safeMode": "",
                        "overrideEndpoint": "",
                        "conditionAgentModel": "chatMistralAI"
                    }
                },
                "outputAnchors": [
                    {
                        "id": "conditionAgentAgentflow_1-output-0",
                        "label": "Condition Agent",
                        "name": "conditionAgentAgentflow"
                    },
                    {
                        "id": "conditionAgentAgentflow_1-output-1",
                        "label": "Condition Agent",
                        "name": "conditionAgentAgentflow"
                    }
                ],
                "outputs": {
                    "conditionAgentAgentflow": ""
                },
                "selected": false
            },
            "type": "agentFlow",
            "width": 228,
            "height": 80,
            "selected": false,
            "positionAbsolute": {
                "x": 966.5436041632489,
                "y": 57.77868724229256
            },
            "dragging": false
        },
        {
            "id": "loopAgentflow_1",
            "position": {
                "x": 1501.0055934843515,
                "y": 140.83809747682727
            },
            "data": {
                "id": "loopAgentflow_1",
                "label": "Recheck SQL Query",
                "version": 1,
                "name": "loopAgentflow",
                "type": "Loop",
                "color": "#FFA07A",
                "hideOutput": true,
                "baseClasses": ["Loop"],
                "category": "Agent Flows",
                "description": "Loop back to a previous node",
                "inputParams": [
                    {
                        "label": "Loop Back To",
                        "name": "loopBackToNode",
                        "type": "asyncOptions",
                        "loadMethod": "listPreviousNodes",
                        "freeSolo": true,
                        "id": "loopAgentflow_1-input-loopBackToNode-asyncOptions",
                        "display": true
                    },
                    {
                        "label": "Max Loop Count",
                        "name": "maxLoopCount",
                        "type": "number",
                        "default": 5,
                        "id": "loopAgentflow_1-input-maxLoopCount-number",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "loopBackToNode": "conditionAgentAgentflow_0-Check SQL Query",
                    "maxLoopCount": 5,
                    "undefined": ""
                },
                "outputAnchors": [],
                "outputs": {},
                "selected": false
            },
            "type": "agentFlow",
            "width": 202,
            "height": 66,
            "selected": false,
            "positionAbsolute": {
                "x": 1501.0055934843515,
                "y": 140.83809747682727
            },
            "dragging": false
        },
        {
            "id": "llmAgentflow_2",
            "position": {
                "x": 1235.4868883628933,
                "y": 137.82100195002667
            },
            "data": {
                "id": "llmAgentflow_2",
                "label": "Regenerate SQL Query",
                "version": 1,
                "name": "llmAgentflow",
                "type": "LLM",
                "color": "#64B5F6",
                "baseClasses": ["LLM"],
                "category": "Agent Flows",
                "description": "Large language models to analyze user-provided inputs and generate responses",
                "inputParams": [
                    {
                        "label": "Model",
                        "name": "llmModel",
                        "type": "asyncOptions",
                        "loadMethod": "listModels",
                        "loadConfig": true,
                        "id": "llmAgentflow_2-input-llmModel-asyncOptions",
                        "display": true
                    },
                    {
                        "label": "Messages",
                        "name": "llmMessages",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Role",
                                "name": "role",
                                "type": "options",
                                "options": [
                                    {
                                        "label": "System",
                                        "name": "system"
                                    },
                                    {
                                        "label": "Assistant",
                                        "name": "assistant"
                                    },
                                    {
                                        "label": "Developer",
                                        "name": "developer"
                                    },
                                    {
                                        "label": "User",
                                        "name": "user"
                                    }
                                ]
                            },
                            {
                                "label": "Content",
                                "name": "content",
                                "type": "string",
                                "acceptVariable": true,
                                "generateInstruction": true,
                                "rows": 4
                            }
                        ],
                        "id": "llmAgentflow_2-input-llmMessages-array",
                        "display": true
                    },
                    {
                        "label": "Enable Memory",
                        "name": "llmEnableMemory",
                        "type": "boolean",
                        "description": "Enable memory for the conversation thread",
                        "default": true,
                        "optional": true,
                        "id": "llmAgentflow_2-input-llmEnableMemory-boolean",
                        "display": true
                    },
                    {
                        "label": "Memory Type",
                        "name": "llmMemoryType",
                        "type": "options",
                        "options": [
                            {
                                "label": "All Messages",
                                "name": "allMessages",
                                "description": "Retrieve all messages from the conversation"
                            },
                            {
                                "label": "Window Size",
                                "name": "windowSize",
                                "description": "Uses a fixed window size to surface the last N messages"
                            },
                            {
                                "label": "Conversation Summary",
                                "name": "conversationSummary",
                                "description": "Summarizes the whole conversation"
                            },
                            {
                                "label": "Conversation Summary Buffer",
                                "name": "conversationSummaryBuffer",
                                "description": "Summarize conversations once token limit is reached. Default to 2000"
                            }
                        ],
                        "optional": true,
                        "default": "allMessages",
                        "show": {
                            "llmEnableMemory": true
                        },
                        "id": "llmAgentflow_2-input-llmMemoryType-options",
                        "display": true
                    },
                    {
                        "label": "Window Size",
                        "name": "llmMemoryWindowSize",
                        "type": "number",
                        "default": "20",
                        "description": "Uses a fixed window size to surface the last N messages",
                        "show": {
                            "llmMemoryType": "windowSize"
                        },
                        "id": "llmAgentflow_2-input-llmMemoryWindowSize-number",
                        "display": false
                    },
                    {
                        "label": "Max Token Limit",
                        "name": "llmMemoryMaxTokenLimit",
                        "type": "number",
                        "default": "2000",
                        "description": "Summarize conversations once token limit is reached. Default to 2000",
                        "show": {
                            "llmMemoryType": "conversationSummaryBuffer"
                        },
                        "id": "llmAgentflow_2-input-llmMemoryMaxTokenLimit-number",
                        "display": false
                    },
                    {
                        "label": "Input Message",
                        "name": "llmUserMessage",
                        "type": "string",
                        "description": "Add an input message as user message at the end of the conversation",
                        "rows": 4,
                        "optional": true,
                        "acceptVariable": true,
                        "show": {
                            "llmEnableMemory": true
                        },
                        "id": "llmAgentflow_2-input-llmUserMessage-string",
                        "display": true
                    },
                    {
                        "label": "Return Response As",
                        "name": "llmReturnResponseAs",
                        "type": "options",
                        "options": [
                            {
                                "label": "User Message",
                                "name": "userMessage"
                            },
                            {
                                "label": "Assistant Message",
                                "name": "assistantMessage"
                            }
                        ],
                        "default": "userMessage",
                        "id": "llmAgentflow_2-input-llmReturnResponseAs-options",
                        "display": true
                    },
                    {
                        "label": "JSON Structured Output",
                        "name": "llmStructuredOutput",
                        "description": "Instruct the LLM to give output in a JSON structured schema",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Key",
                                "name": "key",
                                "type": "string"
                            },
                            {
                                "label": "Type",
                                "name": "type",
                                "type": "options",
                                "options": [
                                    {
                                        "label": "String",
                                        "name": "string"
                                    },
                                    {
                                        "label": "String Array",
                                        "name": "stringArray"
                                    },
                                    {
                                        "label": "Number",
                                        "name": "number"
                                    },
                                    {
                                        "label": "Boolean",
                                        "name": "boolean"
                                    },
                                    {
                                        "label": "Enum",
                                        "name": "enum"
                                    },
                                    {
                                        "label": "JSON Array",
                                        "name": "jsonArray"
                                    }
                                ]
                            },
                            {
                                "label": "Enum Values",
                                "name": "enumValues",
                                "type": "string",
                                "placeholder": "value1, value2, value3",
                                "description": "Enum values. Separated by comma",
                                "optional": true,
                                "show": {
                                    "llmStructuredOutput[$index].type": "enum"
                                }
                            },
                            {
                                "label": "JSON Schema",
                                "name": "jsonSchema",
                                "type": "code",
                                "placeholder": "{\n    \"answer\": {\n        \"type\": \"string\",\n        \"description\": \"Value of the answer\"\n    },\n    \"reason\": {\n        \"type\": \"string\",\n        \"description\": \"Reason for the answer\"\n    },\n    \"optional\": {\n        \"type\": \"boolean\"\n    },\n    \"count\": {\n        \"type\": \"number\"\n    },\n    \"children\": {\n        \"type\": \"array\",\n        \"items\": {\n            \"type\": \"object\",\n            \"properties\": {\n                \"value\": {\n                    \"type\": \"string\",\n                    \"description\": \"Value of the children's answer\"\n                }\n            }\n        }\n    }\n}",
                                "description": "JSON schema for the structured output",
                                "optional": true,
                                "show": {
                                    "llmStructuredOutput[$index].type": "jsonArray"
                                }
                            },
                            {
                                "label": "Description",
                                "name": "description",
                                "type": "string",
                                "placeholder": "Description of the key"
                            }
                        ],
                        "id": "llmAgentflow_2-input-llmStructuredOutput-array",
                        "display": true
                    },
                    {
                        "label": "Update Flow State",
                        "name": "llmUpdateState",
                        "description": "Update runtime state during the execution of the workflow",
                        "type": "array",
                        "optional": true,
                        "acceptVariable": true,
                        "array": [
                            {
                                "label": "Key",
                                "name": "key",
                                "type": "asyncOptions",
                                "loadMethod": "listRuntimeStateKeys",
                                "freeSolo": true
                            },
                            {
                                "label": "Value",
                                "name": "value",
                                "type": "string",
                                "acceptVariable": true,
                                "acceptNodeOutputAsVariable": true
                            }
                        ],
                        "id": "llmAgentflow_2-input-llmUpdateState-array",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "llmModel": "chatAnthropic",
                    "llmMessages": [
                        {
                            "role": "system",
                            "content": "<p>You are an agent designed to interact with a SQL database. Given an input question, create a syntactically correct sqlite query to run, then look at the results of the query and return the answer. Unless the user specifies a specific number of examples they wish to obtain, always limit your query to at most 5 results. You can order the results by a relevant column to return the most interesting examples in the database. Never query for all the columns from a specific table, only ask for the relevant columns given the question. DO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.</p><p>Here is the relevant table info:</p><p><span class=\"variable\" data-type=\"mention\" data-id=\"customFunctionAgentflow_0\" data-label=\"customFunctionAgentflow_0\">{{ customFunctionAgentflow_0 }}</span> </p><p></p>"
                        }
                    ],
                    "llmEnableMemory": true,
                    "llmMemoryType": "allMessages",
                    "llmUserMessage": "<p>Given the generated SQL Query: <span class=\"variable\" data-type=\"mention\" data-id=\"$flow.state.sqlQuery\" data-label=\"$flow.state.sqlQuery\">{{ $flow.state.sqlQuery }}</span> </p><p>I have the following error: <span class=\"variable\" data-type=\"mention\" data-id=\"customFunctionAgentflow_1\" data-label=\"customFunctionAgentflow_1\">{{ customFunctionAgentflow_1 }}</span> </p><p>Regenerate a new SQL Query that will fix the error</p>",
                    "llmReturnResponseAs": "userMessage",
                    "llmStructuredOutput": [
                        {
                            "key": "sql_query",
                            "type": "string",
                            "enumValues": "",
                            "jsonSchema": "",
                            "description": "SQL query"
                        }
                    ],
                    "llmUpdateState": [
                        {
                            "key": "sqlQuery",
                            "value": "<p><span class=\"variable\" data-type=\"mention\" data-id=\"output.sql_query\" data-label=\"output.sql_query\">{{ output.sql_query }}</span> </p>"
                        }
                    ],
                    "llmModelConfig": {
                        "credential": "",
                        "modelName": "claude-sonnet-4-0",
                        "temperature": 0.9,
                        "streaming": true,
                        "maxTokensToSample": "",
                        "topP": "",
                        "topK": "",
                        "extendedThinking": "",
                        "budgetTokens": 1024,
                        "allowImageUploads": "",
                        "llmModel": "chatAnthropic"
                    }
                },
                "outputAnchors": [
                    {
                        "id": "llmAgentflow_2-output-llmAgentflow",
                        "label": "LLM",
                        "name": "llmAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "type": "agentFlow",
            "width": 220,
            "height": 72,
            "selected": false,
            "positionAbsolute": {
                "x": 1235.4868883628933,
                "y": 137.82100195002667
            },
            "dragging": false
        },
        {
            "id": "stickyNoteAgentflow_0",
            "position": {
                "x": 973.4435331695138,
                "y": 156.551869199512
            },
            "data": {
                "id": "stickyNoteAgentflow_0",
                "label": "Sticky Note",
                "version": 1,
                "name": "stickyNoteAgentflow",
                "type": "StickyNote",
                "color": "#fee440",
                "baseClasses": ["StickyNote"],
                "category": "Agent Flows",
                "description": "Add notes to the agent flow",
                "inputParams": [
                    {
                        "label": "",
                        "name": "note",
                        "type": "string",
                        "rows": 1,
                        "placeholder": "Type something here",
                        "optional": true,
                        "id": "stickyNoteAgentflow_0-input-note-string",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "note": "This is an auto correct mechanism that regenerate sql query if result contains error"
                },
                "outputAnchors": [
                    {
                        "id": "stickyNoteAgentflow_0-output-stickyNoteAgentflow",
                        "label": "Sticky Note",
                        "name": "stickyNoteAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "type": "stickyNote",
            "width": 210,
            "height": 123,
            "selected": false,
            "positionAbsolute": {
                "x": 973.4435331695138,
                "y": 156.551869199512
            },
            "dragging": false
        },
        {
            "id": "stickyNoteAgentflow_1",
            "position": {
                "x": 514.8377809033279,
                "y": 200.97994630025966
            },
            "data": {
                "id": "stickyNoteAgentflow_1",
                "label": "Sticky Note (1)",
                "version": 1,
                "name": "stickyNoteAgentflow",
                "type": "StickyNote",
                "color": "#fee440",
                "baseClasses": ["StickyNote"],
                "category": "Agent Flows",
                "description": "Add notes to the agent flow",
                "inputParams": [
                    {
                        "label": "",
                        "name": "note",
                        "type": "string",
                        "rows": 1,
                        "placeholder": "Type something here",
                        "optional": true,
                        "id": "stickyNoteAgentflow_1-input-note-string",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "note": "Check if generated SQL query contains errors/mistakes, if yes - regenerate"
                },
                "outputAnchors": [
                    {
                        "id": "stickyNoteAgentflow_1-output-stickyNoteAgentflow",
                        "label": "Sticky Note",
                        "name": "stickyNoteAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "type": "stickyNote",
            "width": 210,
            "height": 123,
            "selected": false,
            "positionAbsolute": {
                "x": 514.8377809033279,
                "y": 200.97994630025966
            },
            "dragging": false
        },
        {
            "id": "stickyNoteAgentflow_2",
            "position": {
                "x": 40.21835449345774,
                "y": 6.978337213146034
            },
            "data": {
                "id": "stickyNoteAgentflow_2",
                "label": "Sticky Note (1) (2)",
                "version": 1,
                "name": "stickyNoteAgentflow",
                "type": "StickyNote",
                "color": "#fee440",
                "baseClasses": ["StickyNote"],
                "category": "Agent Flows",
                "description": "Add notes to the agent flow",
                "inputParams": [
                    {
                        "label": "",
                        "name": "note",
                        "type": "string",
                        "rows": 1,
                        "placeholder": "Type something here",
                        "optional": true,
                        "id": "stickyNoteAgentflow_2-input-note-string",
                        "display": true
                    }
                ],
                "inputAnchors": [],
                "inputs": {
                    "note": "Retrieve database schema"
                },
                "outputAnchors": [
                    {
                        "id": "stickyNoteAgentflow_2-output-stickyNoteAgentflow",
                        "label": "Sticky Note",
                        "name": "stickyNoteAgentflow"
                    }
                ],
                "outputs": {},
                "selected": false
            },
            "type": "stickyNote",
            "width": 210,
            "height": 82,
            "selected": false,
            "positionAbsolute": {
                "x": 40.21835449345774,
                "y": 6.978337213146034
            },
            "dragging": false
        }
    ],
    "edges": [
        {
            "source": "startAgentflow_0",
            "sourceHandle": "startAgentflow_0-output-startAgentflow",
            "target": "customFunctionAgentflow_0",
            "targetHandle": "customFunctionAgentflow_0",
            "data": {
                "sourceColor": "#7EE787",
                "targetColor": "#E4B7FF",
                "isHumanInput": false
            },
            "type": "agentFlow",
            "id": "startAgentflow_0-startAgentflow_0-output-startAgentflow-customFunctionAgentflow_0-customFunctionAgentflow_0"
        },
        {
            "source": "customFunctionAgentflow_0",
            "sourceHandle": "customFunctionAgentflow_0-output-customFunctionAgentflow",
            "target": "llmAgentflow_0",
            "targetHandle": "llmAgentflow_0",
            "data": {
                "sourceColor": "#E4B7FF",
                "targetColor": "#64B5F6",
                "isHumanInput": false
            },
            "type": "agentFlow",
            "id": "customFunctionAgentflow_0-customFunctionAgentflow_0-output-customFunctionAgentflow-llmAgentflow_0-llmAgentflow_0"
        },
        {
            "source": "llmAgentflow_0",
            "sourceHandle": "llmAgentflow_0-output-llmAgentflow",
            "target": "conditionAgentAgentflow_0",
            "targetHandle": "conditionAgentAgentflow_0",
            "data": {
                "sourceColor": "#64B5F6",
                "targetColor": "#ff8fab",
                "isHumanInput": false
            },
            "type": "agentFlow",
            "id": "llmAgentflow_0-llmAgentflow_0-output-llmAgentflow-conditionAgentAgentflow_0-conditionAgentAgentflow_0"
        },
        {
            "source": "conditionAgentAgentflow_0",
            "sourceHandle": "conditionAgentAgentflow_0-output-0",
            "target": "customFunctionAgentflow_1",
            "targetHandle": "customFunctionAgentflow_1",
            "data": {
                "sourceColor": "#ff8fab",
                "targetColor": "#E4B7FF",
                "edgeLabel": "0",
                "isHumanInput": false
            },
            "type": "agentFlow",
            "id": "conditionAgentAgentflow_0-conditionAgentAgentflow_0-output-0-customFunctionAgentflow_1-customFunctionAgentflow_1"
        },
        {
            "source": "conditionAgentAgentflow_0",
            "sourceHandle": "conditionAgentAgentflow_0-output-1",
            "target": "loopAgentflow_0",
            "targetHandle": "loopAgentflow_0",
            "data": {
                "sourceColor": "#ff8fab",
                "targetColor": "#FFA07A",
                "edgeLabel": "1",
                "isHumanInput": false
            },
            "type": "agentFlow",
            "id": "conditionAgentAgentflow_0-conditionAgentAgentflow_0-output-1-loopAgentflow_0-loopAgentflow_0"
        },
        {
            "source": "customFunctionAgentflow_1",
            "sourceHandle": "customFunctionAgentflow_1-output-customFunctionAgentflow",
            "target": "conditionAgentAgentflow_1",
            "targetHandle": "conditionAgentAgentflow_1",
            "data": {
                "sourceColor": "#E4B7FF",
                "targetColor": "#ff8fab",
                "isHumanInput": false
            },
            "type": "agentFlow",
            "id": "customFunctionAgentflow_1-customFunctionAgentflow_1-output-customFunctionAgentflow-conditionAgentAgentflow_1-conditionAgentAgentflow_1"
        },
        {
            "source": "conditionAgentAgentflow_1",
            "sourceHandle": "conditionAgentAgentflow_1-output-0",
            "target": "llmAgentflow_1",
            "targetHandle": "llmAgentflow_1",
            "data": {
                "sourceColor": "#ff8fab",
                "targetColor": "#64B5F6",
                "edgeLabel": "0",
                "isHumanInput": false
            },
            "type": "agentFlow",
            "id": "conditionAgentAgentflow_1-conditionAgentAgentflow_1-output-0-llmAgentflow_1-llmAgentflow_1"
        },
        {
            "source": "conditionAgentAgentflow_1",
            "sourceHandle": "conditionAgentAgentflow_1-output-1",
            "target": "llmAgentflow_2",
            "targetHandle": "llmAgentflow_2",
            "data": {
                "sourceColor": "#ff8fab",
                "targetColor": "#64B5F6",
                "edgeLabel": "1",
                "isHumanInput": false
            },
            "type": "agentFlow",
            "id": "conditionAgentAgentflow_1-conditionAgentAgentflow_1-output-1-llmAgentflow_2-llmAgentflow_2"
        },
        {
            "source": "llmAgentflow_2",
            "sourceHandle": "llmAgentflow_2-output-llmAgentflow",
            "target": "loopAgentflow_1",
            "targetHandle": "loopAgentflow_1",
            "data": {
                "sourceColor": "#64B5F6",
                "targetColor": "#FFA07A",
                "isHumanInput": false
            },
            "type": "agentFlow",
            "id": "llmAgentflow_2-llmAgentflow_2-output-llmAgentflow-loopAgentflow_1-loopAgentflow_1"
        }
    ]
}
